Overnight-Intraday Weekly Reversal in Interest Rate Futures

1from AlgorithmImports import *
2class OvernightIntradayWeeklyReversalInterestRate(QCAlgorithm):
3def Initialize(self):
4 self.SetStartDate(2000, 1, 1)
5 self.SetCash(100000)
6 
7 self.symbols = [
8     "CME_TY1",      # 10 Yr Note Futures, Continuous Contract #1
9     "CME_FV1",      # 5 Yr Note Futures, Continuous Contract #1
10     "CME_TU1"       # 2 Yr Note Futures, Continuous Contract #1
11     "CME_ED1",      # Eurodollar Futures, Continuous Contract #1
12     "CME_FF1",      # 30-Day Fed Funds Futures, Continuous Contract #1
13     "CME_US1"       # US Treasury Bond Futures, Continuous Contract #1
14     "CME_UT1"       # US Ultra T-Bond Bond Futures, Continuous Contract #1                        
15 ]
16 
17 self.friday_close = {}
18 self.leverage = 1
19 
20 for symbol in self.symbols:
21     data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
22     data.SetFeeModel(CustomFeeModel())
23     data.SetLeverage(5)
24     self.friday_close[symbol] = 0
25 
26 self.settings.minimum_order_margin_portfolio_percentage = 0.
27def OnData(self, data):
28 # Saturday -> Friday close available
29 if self.Time.date().weekday() == 5:
30     for symbol in self.symbols:
31         if symbol in data and data[symbol]:
32             price = data[symbol].Value
33             if price != 0:
34                 self.friday_close[symbol] = price
35             
36     self.Liquidate()
37 # Tuesday -> Monday close available
38 elif self.Time.date().weekday() == 1:
39     returns = {}
40     
41     for symbol in self.symbols:
42         # Check if data is still coming.
43         if self.securities[symbol].get_last_data() and self.time.date() > QuantpediaFutures.get_last_update_date()[symbol]:
44             self.liquidate(symbol)
45             continue
46         if symbol in data and data[symbol]:
47             price = data[symbol].Value
48             if price != 0 and symbol in self.friday_close and self.friday_close[symbol] != 0:
49                 returns[symbol] = price / self.friday_close[symbol] - 1
50     
51     self.friday_close.clear()
52     if len(returns) == 0: 
53         return
54     
55     ret_mean = np.mean([x[1] for x in returns.items()])
56     
57     weight = {}
58     N = len(returns)
59     for symbol in returns:
60         weight[symbol] = -(1/N) * (returns[symbol] - ret_mean) * 100
61
62     for symbol in weight:
63         if data.contains_key(symbol) and data[symbol]:
64             self.SetHoldings(symbol, self.leverage * weight[symbol])
65# Quantpedia data.
66# NOTE: IMPORTANT: Data order must be ascending (datewise)
67class QuantpediaFutures(PythonData):
68_last_update_date:Dict[Symbol, datetime.date] = {}
69@staticmethod
70def get_last_update_date() -> Dict[Symbol, datetime.date]:
71return QuantpediaFutures._last_update_date
72def GetSource(self, config, date, isLiveMode):
73 return SubscriptionDataSource("data.quantpedia.com/backtesting_data/futures/{0}.csv".format(config.Symbol.Value), SubscriptionTransportMedium.RemoteFile, FileFormat.Csv)
74def Reader(self, config, line, date, isLiveMode):
75 data = QuantpediaFutures()
76 data.Symbol = config.Symbol
77 
78 if not line[0].isdigit(): return None
79 split = line.split(';')
80 
81 data.Time = datetime.strptime(split[0], "%d.%m.%Y") + timedelta(days=1)
82 data['back_adjusted'] = float(split[1])
83 data['spliced'] = float(split[2])
84 data.Value = float(split[1])
85 if config.Symbol.Value not in QuantpediaFutures._last_update_date:
86     QuantpediaFutures._last_update_date[config.Symbol.Value] = datetime(1,1,1).date()
87 if data.Time.date() > QuantpediaFutures._last_update_date[config.Symbol.Value]:
88     QuantpediaFutures._last_update_date[config.Symbol.Value] = data.Time.date()
89     
90 return data
91# Custom fee model.
92class CustomFeeModel(FeeModel):
93def GetOrderFee(self, parameters):
94 fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
95 return OrderFee(CashAmount(fee, "USD"))